1. Field of the Invention
The invention is related to the field of communications, and in particular, to the management of data storage systems for a communication network.
2. Description of the Prior Art
A communication network provides various communication services to network users. A few examples of communication networks include public switched networks, wireless access networks, and Internet networks. A few examples of communication services include voice communications, data transfer, video delivery, and Internet access.
The operation of a communication network produces vast quantities of data that need to be stored. To provide the data storage, the communications network includes a storage infrastructure that includes a wide array of storage equipment and software. Typically, the storage equipment and software are provided by a diverse set of suppliers. Each supplier has their own management system for their products. Unfortunately, the result is a complex set of storage equipment and software with numerous individual management systems. In a large communication network, this type of complex storage infrastructure is difficult and expensive to manage.
The communication network also employs various personnel to plan, deploy, and operate the storage infrastructure. The complexity of the storage infrastructure is often reflected in a complex set of personnel that are responsible for various aspects of the storage infrastructure. In such a complex personnel organizational structure, some important storage tasks may be under-worked, while less important tasks may be overworked, or worse, redundantly performed by overlapping organizations.
The result of this complex storage infrastructure is often wasted expense and inefficiency. The management of the storage infrastructure and personnel in a communication network has not developed any systematic approach that decreases cost and improves efficiency. Improved tools for managing storage infrastructures and personnel are needed.
For example, when the communication network produces a new data flow for storage, the selection of the appropriate storage system for data may be uninformed.
Storage personnel may not properly consider all factors before making the selection. A typical result is that less important data uses up capacity on the best storage system, when that capacity should be reserved for more important data.
In another example, the storage infrastructure typically develops over time in terms of personnel and technology. Decisions regarding which technology to deploy are often made without a clear and detailed view of what technology is most needed. Thus, the decisions regarding the deployment of new technology in the complex storage infrastructure are often uninformed decisions. Likewise, decisions regarding which personnel to deploy are often made without a clear and detailed view of what is most needed. New tools are needed to improve decision making related to how new personnel and technology are utilized.
In another example, the storage infrastructure may become vary large and complex. The size and complexity of the infrastructure results in massive costs. The ability to analyze these massive costs to ensure a return on investment is difficult. Effective cost models are needed to allow the analysis of costs at various levels and perspectives.
In another example, the storage infrastructure may require a large employee base with various skills and tasks. The size and complexity of the employee base can make it difficult to decide how to use the employees. Effective employee models are needed to allow the analysis of employee effectiveness at various levels and perspectives.
In another example, the storage infrastructure may require a vast amount of equipment and software. The size and complexity of the infrastructure can make it difficult to track and maintain the equipment and software in the infrastructure. Effective infrastructure models are needed to track the components of the storage infrastructure.
In another example, the storage infrastructure requires funding for maintenance and growth. The size and complexity of the infrastructure can make it difficult to forecast and track funding requirements. Effective scheduling information for funding is needed.
In another example, the storage infrastructure is typically under constant change as new systems are planned, tested, and operated. The size and complexity of the infrastructure can make it difficult to track the current status of applications and systems. Information on the status of applications and systems is needed.